Nothing
bosplot1 <- function(object){
m <- object@m
nb.V <- length(unique(object@zr))
gammas <- rep(0,nb.V)
for(i in 1:nb.V){
gammas[i] <- length(which(object@zr==i))/length(object@zr)
}
if(object@name == "ClassifM"){
D <- length(m)
par(mfrow=c(1,D))
for(id in 1:D){
tmp <- object@xhat[[id]][sort(object@zr,index.return=TRUE)$ix,1:ncol(object@xhat[[id]])]
par(xpd=TRUE, mar=c(2,1,4,7))
image(t(tmp),xaxt='n',yaxt='n', main='classification',cex.main=1.5,col = gray(m[id]:1/m[id]))
legend(x=1.01,y=0.65,legend = 1:m[id],col = gray(m[id]:1/m[id]),pch=15,bty="n",cex=1)
par(xpd=FALSE)
sum.gammas <- 0
for(i in 1:(nb.V-1)){
sum.gammas <- sum.gammas + gammas[i]
abline(h=sum.gammas,lwd=3, col="red")
}
}
}
if(object@name == "Classif"){
D <- length(m)
par(mfrow=c(1,D))
for(id in 1:D){
tmp <- object@xhat[[id]][sort(object@zr,index.return=TRUE)$ix,
sort(object@zc[[id]],index.return=TRUE)$ix]
par(xpd=TRUE, mar=c(2,1,4,7))
image(t(tmp),xaxt='n',yaxt='n', main='classification',cex.main=1.5,col = gray(m[id]:1/m[id]))
legend(x=1.01,y=0.65,legend = 1:m[id],col = gray(m[id]:1/m[id]),pch=15,bty="n",cex=1)
par(xpd=FALSE)
nb.W <- length(unique(object@zc[[id]]))
sum.rho <- 0
if(nb.W!=1){
for(i in 1:(nb.W-1)){
rho <- length(which(object@zc[[id]]==i))/length(object@zc[[id]])
sum.rho <- sum.rho + rho
abline(v=sum.rho,lwd=3, col="red")
}
}
sum.gammas <- 0
for(i in 1:(nb.V-1)){
sum.gammas <- sum.gammas + gammas[i]
abline(h=sum.gammas,lwd=3, col="red")
}
}
}
if(object@name == "Coclust"){
D <- length(m)
par(mfrow=c(1,D))
for(id in 1:D){
tmp <- object@xhat[[id]][sort(object@zr,index.return=TRUE)$ix,
sort(object@zc[[id]],index.return=TRUE)$ix]
par(xpd=TRUE, mar=c(2,1,4,7))
image(t(tmp),xaxt='n',yaxt='n', main='co-clustering',cex.main=1.5,col = gray(m[id]:1/m[id]))
legend(x=1.01,y=0.65,legend = 1:m[id],col = gray(m[id]:1/m[id]),pch=15,bty="n",cex=1)
par(xpd=FALSE)
nb.W <- length(unique(object@zc[[id]]))
sum.rho <- 0
if(nb.W!=1){
for(i in 1:(nb.W-1)){
rho <- length(which(object@zc[[id]]==i))/length(object@zc[[id]])
sum.rho <- sum.rho + rho
abline(v=sum.rho,lwd=3, col="red")
}
}
sum.gammas <- 0
for(i in 1:(nb.V-1)){
sum.gammas <- sum.gammas + gammas[i]
abline(h=sum.gammas,lwd=3, col="red")
}
}
}
if(object@name == "Clust"){
D <- length(m)
par(mfrow=c(1,D))
for(id in 1:D){
tmp <- object@xhat[[id]][sort(object@zr,index.return=TRUE)$ix,1:ncol(object@xhat[[id]])]
image(t(tmp),xaxt='n',yaxt='n', main='clustering',cex.main=1.5,col = gray(m[id]:1/m[id]))
par(xpd=TRUE, mar=c(2,1,4,7))
legend(x=1.01,y=0.65,legend = 1:m[id],col = gray(m[id]:1/m[id]),pch=15,bty="n",cex=1)
par(xpd=FALSE)
sum.gammas <- 0
for(i in 1:(nb.V-1)){
sum.gammas <- sum.gammas + gammas[i]
abline(h=sum.gammas,lwd=3, col="red")
}
}
}
}
bosplot <- function(object){
par(xpd=TRUE, mar=c(2,1,4,7))
par(xpd=FALSE)
m <- object@m
nb.V <- length(unique(object@zr))
gammas <- rep(0,nb.V)
for(i in 1:nb.V){
gammas[i] <- length(which(object@zr==i))/length(object@zr)
}
if(object@name == "ClassifM"){
D <- length(m)
par(mfrow=c(1,D))
for(id in 1:D){
tmp <- object@xhat[[id]][sort(object@zr,index.return=TRUE)$ix,1:ncol(object@xhat[[id]])]
par(xpd=TRUE, mar=c(2,1,4,7))
image(t(tmp),xaxt='n',yaxt='n', main='classification',cex.main=1.5,col = gray(m[id]:1/m[id]))
legend(x=1.01,y=0.65,legend = 1:m[id],col = gray(m[id]:1/m[id]),pch=15,bty="n",cex=1)
par(xpd=FALSE)
sum.gammas <- 0
for(i in 1:(nb.V-1)){
sum.gammas <- sum.gammas + gammas[i]
abline(h=sum.gammas,lwd=3, col="red")
}
}
}
if(object@name == "Classif"){
D <- length(m)
par(mfrow=c(1,D))
for(id in 1:D){
tmp <- object@xhat[[id]][sort(object@zr,index.return=TRUE)$ix,
sort(object@zc[[id]],index.return=TRUE)$ix]
par(xpd=TRUE, mar=c(2,1,4,7))
image(t(tmp),xaxt='n',yaxt='n', main='classification',cex.main=1.5,col = gray(m[id]:1/m[id]))
legend(x=1.01,y=0.65,legend = 1:m[id],col = gray(m[id]:1/m[id]),pch=15,bty="n",cex=1)
par(xpd=FALSE)
nb.W <- length(unique(object@zc[[id]]))
sum.rho <- 0
if(nb.W!=1){
for(i in 1:(nb.W-1)){
rho <- length(which(object@zc[[id]]==i))/length(object@zc[[id]])
sum.rho <- sum.rho + rho
abline(v=sum.rho,lwd=3, col="red")
}
}
sum.gammas <- 0
for(i in 1:(nb.V-1)){
sum.gammas <- sum.gammas + gammas[i]
abline(h=sum.gammas,lwd=3, col="red")
}
}
}
if(object@name == "Coclust"){
D <- length(m)
par(mfrow=c(1,D))
for(id in 1:D){
tmp <- object@xhat[[id]][sort(object@zr,index.return=TRUE)$ix,
sort(object@zc[[id]],index.return=TRUE)$ix]
par(xpd=TRUE, mar=c(2,1,4,7))
image(t(tmp),xaxt='n',yaxt='n', main='co-clustering',cex.main=1.5,col = gray(m[id]:1/m[id]))
legend(x=1.01,y=0.65,legend = 1:m[id],col = gray(m[id]:1/m[id]),pch=15,bty="n",cex=1)
par(xpd=FALSE)
nb.W <- length(unique(object@zc[[id]]))
sum.rho <- 0
if(nb.W!=1){
for(i in 1:(nb.W-1)){
rho <- length(which(object@zc[[id]]==i))/length(object@zc[[id]])
sum.rho <- sum.rho + rho
abline(v=sum.rho,lwd=3, col="red")
}
}
sum.gammas <- 0
for(i in 1:(nb.V-1)){
sum.gammas <- sum.gammas + gammas[i]
abline(h=sum.gammas,lwd=3, col="red")
}
}
}
if(object@name == "Clust"){
D <- length(m)
par(mfrow=c(1,D))
for(id in 1:D){
tmp <- object@xhat[[id]][sort(object@zr,index.return=TRUE)$ix,1:ncol(object@xhat[[id]])]
image(t(tmp),xaxt='n',yaxt='n', main='clustering',cex.main=1.5,col = gray(m[id]:1/m[id]))
par(xpd=TRUE, mar=c(2,1,4,7))
legend(x=1.01,y=0.65,legend = 1:m[id],col = gray(m[id]:1/m[id]),pch=15,bty="n",cex=1)
par(xpd=FALSE)
sum.gammas <- 0
for(i in 1:(nb.V-1)){
sum.gammas <- sum.gammas + gammas[i]
abline(h=sum.gammas,lwd=3, col="red")
}
}
}
}
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